ROADS

   Based on a HPC cloud service, LiDARitmanager.AI will perform a rigorous step by step LiDAR post processing to deliver the final land survey CAD drawings, products and measurements. Supervised in the critical stages, it includes a report made by experts.

LiDAR post processing start with PPK GNSS-INS best accurate trajectory estimation (With GNSS base station observations and precision ephemeris) for a trajectory or traverse closure error less than 8mm, then the accuracy point cloud creation, fluctuations adjustment between lines when satellite signals are blocked or unavailable, Point Cloud Classification and finally the LiDAR deliverables generation.  

   In order to be efficient in the field, the unit has the IMU permanently attached to the rear face of the LiDAR. This allows, with an initial calibration, to carry out different projects without requiring additional calibration flights for each of the recording sessions within the projects. The calibration process carried out by LiDARit experts consists of an initial flight at the maximum recommended height in several parallel lines, crossed with another set of lines parallel and perpendicular to the initial one, and other roundtrip lines made on the same axis. It is carried out on clean surfaces of vegetation such as roads with road markings on the road and some nearby buildings.  

In the process, the angular variation in pitch is corrected first by identifying objects located on the central axis between two parallel lines not aligned at the same height. This object located on this axis is not affected by angular variations of Roll or Heading.  

After having corrected the angular variation in Pitch, the angular correction in roll is then carried out by taking an object that is located on the axis of two parallel lines coinciding with the same flight height in round trip. On this axis, the angular variation in Roll is calculated since it is not affected by the variation in Heading or by the variation in Pitch, which was previously corrected.  

Finally, two perpendicular flight lines are selected and an object is identified that is aligned on one of the two lines and that is far enough away from the second to adjust the variation in Heading. The recommended equipment calibration frequency is one year or 1,200 hours of use, whichever comes first. Each calibration is delivered with the certificate issued from LiDARit.  

  LiDARit units use Real Time Kinematic positioning for the most precise measurements (cm level), relative to a local surveyed base station network. RTK is a relative positioning method that provides the position of one receiver antenna (the “rover”) relative to another receiver antenna (the “base”). If the location of the base receiver is known, an absolute position of the rover can be estimated. Most error sources are common to both the rover and base receivers, and therefore can be mitigated by differencing measurements across receivers. This reduces the magnitude of the errors significantly when the distance (baseline) between receivers is not long. The length of the baseline must typically be 40 km or less to enable RTK carrier-phase ambiguity resolution when ionospheric conditions are not extreme.   

LiDARit use Inertial Explorer software that is compatible with the Novatel GNSS/INS receiver used into the LiDARit unit, to maximizes the performance of the GNSS/INS hardware by ensuring getting the position, velocity and attitude accuracy that the project requires. The tightly coupled integration of GNSS and IMU data delivers precise results.  

For static positioning of the base antenna, the information of geographical coordinates, ellipsoidal height and instrumental height is used to fit the survey traverse trajectory between ROVER and base antenna used for the correction process. When processing kinematic and static data, the precise coordinate and height where the antenna was located for the area of interest is entered; This is to ensure that the information file obtained by ROVER has a network closure throughout its entire trajectory and centimeter-level precision is quickly achieved in processing environments.  

The angular variation values are verified for roll and pitch below a value of 1 arcmin and for heading a limit value of 1.5 arcmin.  

The straight sections of the flights are initially classified, excluding turns outside the polygon before generating the clouds to avoid having a high angular variation value within the generated cloud. Point clouds are generated for each recording session and the project is created with all the clouds generated.  

   After generating the point cloud on the LiDARit manager server, the project is created in the specialized software for Point cloud handle called Terrasolid. A first classification of flight lines is carried out and later, using terrain classification algorithms, it is separated into two classes, the vegetation, buildings and objects in a class called No Terrain and the points located in the lower layer of the cloud in the Terrain class . Due to the number of points, a subdivision into blocks of 40 million points is made to advance block processing. Tie lines are defined for adjustments and finally the final point cloud result is obtained to generate the various products such as DTM, DSM, contour lines, and classified cloud.  

Additional adjustments required by the project are made. For instance, the required projections for each project are made using the geoid or PRJ file to project according to the system required for the project. In cases where photos are included during the flight, these are synchronized by an identifier stored in the flight log file inside the GNSS receiver, which allows knowing the precise coordinates of each photo in the post-processing stage, obtaining metadata for the photographs later. to perform the ARTK correction process. Finally, color is added to the point cloud using the previously created and georeferenced orthophoto.  

  Prior to data processing, there is a first verification carried out in the field, verifying the recorded data using the LiDARit Reader software.  

When uploading the data to the lidaritmanger, the data is verified to be complete and that the Rinex base antenna files correspond to the period of time during which the data was recorded with the LiDARit equipment.  

After finishing the trajectory correction process, the positional error calculated by means of the ASPRS equation defined as:   

Lidar error (RMSE)2 = (GNSS Positional error)2 + (tan (IMUerror) / 0.5589170 * Flight height)2 

The result of this value is compared with that required in the project to validate and advance to the next stage of processing.  

Finally, with the control points provided for the project, the accuracy of the project at these points is validated and registered in a project report that is published in the site lidaritmanager.ai in the project section.  

 After having established an ideal configuration to classify the terrain, we use the attribute of "elevation" to create a surface which uses an irregular triangulated network that connects the known elevation values, in this case the points to be used have another attribute " classification ”for this product corresponding to class 2 or Ground (ASPRS). Resolution 0.2 meters. 

 In this case, the points to be used to carry out the model (triangulation) correspond if the classification is standard to: “Ground” and “Created, never classified”, in case the classification applied to the cloud is complete, the corresponding classes. Resolution 0.2 meters. 

 The digital terrain model is entered, the parameters with which the curves will be generated are configured, such as the interval (0.20mts, 0.5mts and 1mt), the smoothing (prevents the lines from being too sharp), the curves are discarded of level that are very closed (30mts), depending on the terrain; Next, the result is exported to the .DWG format where the units, the color of the major, intermediate and minor curves are set and the corresponding projection is assigned. 

 The software used for the classification, allows to include the geoid supplied by the client to perform the calculations of the undulations that are going to be applied to the point cloud, since the geoid is large, we have the possibility of establishing limits close to the zone to be able to carry out the process more quickly, so that when performing the triangulations of both DTM and DSM, these would already be corrected.